Overview

Dataset statistics

Number of variables17
Number of observations185
Missing cells705
Missing cells (%)22.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.7 KiB
Average record size in memory136.7 B

Variable types

Numeric5
Text7
Categorical1
DateTime3
Unsupported1

Alerts

airdate has constant value ""Constant
id_embedded is highly overall correlated with seasonHigh correlation
season is highly overall correlated with id_embeddedHigh correlation
number is highly overall correlated with typeHigh correlation
type is highly overall correlated with numberHigh correlation
type is highly imbalanced (87.5%)Imbalance
number has 5 (2.7%) missing valuesMissing
airtime has 128 (69.2%) missing valuesMissing
runtime has 27 (14.6%) missing valuesMissing
rating_average has 185 (100.0%) missing valuesMissing
medium has 119 (64.3%) missing valuesMissing
original has 119 (64.3%) missing valuesMissing
summary has 122 (65.9%) missing valuesMissing
id has unique valuesUnique
url has unique valuesUnique
_links_self has unique valuesUnique
rating_average is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-08-06 02:56:46.958488
Analysis finished2023-08-06 02:56:50.478667
Duration3.52 seconds
Software versionydata-profiling vv4.4.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

UNIQUE 

Distinct185
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2457452
Minimum2164183
Maximum2607659
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:50.567408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2164183
5-th percentile2401592.8
Q12436792
median2453016
Q32461142
95-th percentile2569274.8
Maximum2607659
Range443476
Interquartile range (IQR)24350

Descriptive statistics

Standard deviation53778.5
Coefficient of variation (CV)0.021883846
Kurtosis5.5594625
Mean2457452
Median Absolute Deviation (MAD)10279
Skewness0.19389748
Sum4.5462862 × 108
Variance2.892127 × 109
MonotonicityNot monotonic
2023-08-05T21:56:50.734480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2401588 1
 
0.5%
2569272 1
 
0.5%
2417927 1
 
0.5%
2327477 1
 
0.5%
2454086 1
 
0.5%
2454097 1
 
0.5%
2454116 1
 
0.5%
2569268 1
 
0.5%
2569269 1
 
0.5%
2569270 1
 
0.5%
Other values (175) 175
94.6%
ValueCountFrequency (%)
2164183 1
0.5%
2327477 1
0.5%
2355092 1
0.5%
2372684 1
0.5%
2393550 1
0.5%
2395106 1
0.5%
2397090 1
0.5%
2399224 1
0.5%
2401021 1
0.5%
2401588 1
0.5%
ValueCountFrequency (%)
2607659 1
0.5%
2607235 1
0.5%
2607234 1
0.5%
2603387 1
0.5%
2576026 1
0.5%
2576025 1
0.5%
2575564 1
0.5%
2575563 1
0.5%
2572526 1
0.5%
2569275 1
0.5%

id_embedded
Real number (ℝ)

HIGH CORRELATION 

Distinct111
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57134.097
Minimum851
Maximum70186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:50.892910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum851
5-th percentile36764.2
Q153288
median63487
Q365931
95-th percentile67584.6
Maximum70186
Range69335
Interquartile range (IQR)12643

Descriptive statistics

Standard deviation13177.627
Coefficient of variation (CV)0.23064383
Kurtosis5.1942162
Mean57134.097
Median Absolute Deviation (MAD)2746
Skewness-2.1331871
Sum10569808
Variance1.7364986 × 108
MonotonicityNot monotonic
2023-08-05T21:56:51.197201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50036 8
 
4.3%
62659 8
 
4.3%
53449 8
 
4.3%
64517 8
 
4.3%
65966 7
 
3.8%
66165 6
 
3.2%
55631 6
 
3.2%
47480 6
 
3.2%
65471 4
 
2.2%
66199 4
 
2.2%
Other values (101) 120
64.9%
ValueCountFrequency (%)
851 1
0.5%
3390 1
0.5%
5493 1
0.5%
7847 1
0.5%
13215 1
0.5%
16753 1
0.5%
17046 1
0.5%
24963 1
0.5%
28381 1
0.5%
36745 1
0.5%
ValueCountFrequency (%)
70186 2
1.1%
69463 2
1.1%
69351 1
0.5%
69238 2
1.1%
68784 1
0.5%
67907 1
0.5%
67776 1
0.5%
66819 1
0.5%
66441 1
0.5%
66248 1
0.5%

url
Text

UNIQUE 

Distinct185
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:51.464480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length128
Median length102
Mean length77.481081
Min length58

Characters and Unicode

Total characters14334
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)100.0%

Sample

1st rowhttps://www.tvmaze.com/episodes/2401588/po-sezonu-videodajdzest-seasonvar-8x51-vypusk-409
2nd rowhttps://www.tvmaze.com/episodes/2164183/smesariki-novyj-sezon-1x100-sinema
3rd rowhttps://www.tvmaze.com/episodes/2575563/hocu-vse-znat-2x93-seria-93
4th rowhttps://www.tvmaze.com/episodes/2575564/hocu-vse-znat-2x94-seria-94
5th rowhttps://www.tvmaze.com/episodes/2443147/manuna-2x03-seria-3
ValueCountFrequency (%)
https://www.tvmaze.com/episodes/2401588/po-sezonu-videodajdzest-seasonvar-8x51-vypusk-409 1
 
0.5%
https://www.tvmaze.com/episodes/2448457/13-kliniceskaa-1x01-seria-1 1
 
0.5%
https://www.tvmaze.com/episodes/2449288/the-director-who-buys-me-dinner-1x04-episode-4 1
 
0.5%
https://www.tvmaze.com/episodes/2575563/hocu-vse-znat-2x93-seria-93 1
 
0.5%
https://www.tvmaze.com/episodes/2575564/hocu-vse-znat-2x94-seria-94 1
 
0.5%
https://www.tvmaze.com/episodes/2443147/manuna-2x03-seria-3 1
 
0.5%
https://www.tvmaze.com/episodes/2443148/manuna-2x04-seria-4 1
 
0.5%
https://www.tvmaze.com/episodes/2424822/s-nula-1x07-seria-07 1
 
0.5%
https://www.tvmaze.com/episodes/2452406/martyskiny-1x19-martyskin-gol 1
 
0.5%
https://www.tvmaze.com/episodes/2452409/martyskiny-1x20-v-gostah-u-paporotnika 1
 
0.5%
Other values (175) 175
94.6%
2023-08-05T21:56:51.919747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1226
 
8.6%
- 1085
 
7.6%
/ 925
 
6.5%
s 911
 
6.4%
t 852
 
5.9%
o 711
 
5.0%
a 616
 
4.3%
w 611
 
4.3%
i 598
 
4.2%
p 538
 
3.8%
Other values (30) 6261
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9691
67.6%
Decimal Number 2078
 
14.5%
Other Punctuation 1480
 
10.3%
Dash Punctuation 1085
 
7.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1226
12.7%
s 911
 
9.4%
t 852
 
8.8%
o 711
 
7.3%
a 616
 
6.4%
w 611
 
6.3%
i 598
 
6.2%
p 538
 
5.6%
m 489
 
5.0%
d 424
 
4.4%
Other values (16) 2715
28.0%
Decimal Number
ValueCountFrequency (%)
2 410
19.7%
1 351
16.9%
4 335
16.1%
0 217
10.4%
5 171
8.2%
3 161
 
7.7%
6 134
 
6.4%
7 117
 
5.6%
8 97
 
4.7%
9 85
 
4.1%
Other Punctuation
ValueCountFrequency (%)
/ 925
62.5%
. 370
 
25.0%
: 185
 
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 1085
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9691
67.6%
Common 4643
32.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1226
12.7%
s 911
 
9.4%
t 852
 
8.8%
o 711
 
7.3%
a 616
 
6.4%
w 611
 
6.3%
i 598
 
6.2%
p 538
 
5.6%
m 489
 
5.0%
d 424
 
4.4%
Other values (16) 2715
28.0%
Common
ValueCountFrequency (%)
- 1085
23.4%
/ 925
19.9%
2 410
 
8.8%
. 370
 
8.0%
1 351
 
7.6%
4 335
 
7.2%
0 217
 
4.7%
: 185
 
4.0%
5 171
 
3.7%
3 161
 
3.5%
Other values (4) 433
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14334
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1226
 
8.6%
- 1085
 
7.6%
/ 925
 
6.5%
s 911
 
6.4%
t 852
 
5.9%
o 711
 
5.0%
a 616
 
4.3%
w 611
 
4.3%
i 598
 
4.2%
p 538
 
3.8%
Other values (30) 6261
43.7%

name
Text

Distinct144
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:52.280014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length67
Median length53
Mean length14.881081
Min length3

Characters and Unicode

Total characters2753
Distinct characters130
Distinct categories12 ?
Distinct scripts5 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique125 ?
Unique (%)67.6%

Sample

1st rowВыпуск 409
2nd rowСинема
3rd rowСерия 93
4th rowСерия 94
5th rowСерия 3
ValueCountFrequency (%)
episode 69
 
13.2%
the 21
 
4.0%
серия 18
 
3.4%
4 13
 
2.5%
1 10
 
1.9%
3 9
 
1.7%
2 8
 
1.5%
chapter 8
 
1.5%
8 7
 
1.3%
of 7
 
1.3%
Other values (285) 353
67.5%
2023-08-05T21:56:52.821651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
338
 
12.3%
e 227
 
8.2%
i 149
 
5.4%
o 144
 
5.2%
s 125
 
4.5%
d 108
 
3.9%
a 107
 
3.9%
p 104
 
3.8%
E 94
 
3.4%
r 91
 
3.3%
Other values (120) 1266
46.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1761
64.0%
Uppercase Letter 400
 
14.5%
Space Separator 338
 
12.3%
Decimal Number 177
 
6.4%
Other Punctuation 32
 
1.2%
Other Letter 32
 
1.2%
Dash Punctuation 8
 
0.3%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Other Symbol 1
 
< 0.1%
Other values (2) 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 227
12.9%
i 149
 
8.5%
o 144
 
8.2%
s 125
 
7.1%
d 108
 
6.1%
a 107
 
6.1%
p 104
 
5.9%
r 91
 
5.2%
t 82
 
4.7%
n 74
 
4.2%
Other values (47) 550
31.2%
Uppercase Letter
ValueCountFrequency (%)
E 94
23.5%
T 32
 
8.0%
D 28
 
7.0%
С 19
 
4.8%
I 19
 
4.8%
C 18
 
4.5%
A 18
 
4.5%
S 18
 
4.5%
N 16
 
4.0%
R 15
 
3.8%
Other values (27) 123
30.8%
Other Letter
ValueCountFrequency (%)
ل 7
21.9%
ا 6
18.8%
ة 4
12.5%
ح 3
9.4%
ق 3
9.4%
س 2
 
6.2%
ع 2
 
6.2%
ي 2
 
6.2%
ب 1
 
3.1%
ن 1
 
3.1%
Decimal Number
ValueCountFrequency (%)
1 48
27.1%
2 28
15.8%
4 26
14.7%
3 18
 
10.2%
7 12
 
6.8%
8 11
 
6.2%
0 10
 
5.6%
5 9
 
5.1%
6 8
 
4.5%
9 7
 
4.0%
Other Punctuation
ValueCountFrequency (%)
: 13
40.6%
. 6
18.8%
" 4
 
12.5%
, 4
 
12.5%
' 2
 
6.2%
! 2
 
6.2%
/ 1
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 7
87.5%
1
 
12.5%
Space Separator
ValueCountFrequency (%)
338
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Math Symbol
ValueCountFrequency (%)
| 1
100.0%
Nonspacing Mark
ValueCountFrequency (%)
ً 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1885
68.5%
Common 559
 
20.3%
Cyrillic 276
 
10.0%
Arabic 32
 
1.2%
Inherited 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 227
 
12.0%
i 149
 
7.9%
o 144
 
7.6%
s 125
 
6.6%
d 108
 
5.7%
a 107
 
5.7%
p 104
 
5.5%
E 94
 
5.0%
r 91
 
4.8%
t 82
 
4.4%
Other values (43) 654
34.7%
Cyrillic
ValueCountFrequency (%)
и 34
12.3%
е 26
 
9.4%
р 25
 
9.1%
я 25
 
9.1%
С 19
 
6.9%
а 17
 
6.2%
о 15
 
5.4%
н 12
 
4.3%
с 11
 
4.0%
т 9
 
3.3%
Other values (31) 83
30.1%
Common
ValueCountFrequency (%)
338
60.5%
1 48
 
8.6%
2 28
 
5.0%
4 26
 
4.7%
3 18
 
3.2%
: 13
 
2.3%
7 12
 
2.1%
8 11
 
2.0%
0 10
 
1.8%
5 9
 
1.6%
Other values (14) 46
 
8.2%
Arabic
ValueCountFrequency (%)
ل 7
21.9%
ا 6
18.8%
ة 4
12.5%
ح 3
9.4%
ق 3
9.4%
س 2
 
6.2%
ع 2
 
6.2%
ي 2
 
6.2%
ب 1
 
3.1%
ن 1
 
3.1%
Inherited
ValueCountFrequency (%)
ً 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2435
88.4%
Cyrillic 276
 
10.0%
Arabic 33
 
1.2%
None 7
 
0.3%
Letterlike Symbols 1
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
338
 
13.9%
e 227
 
9.3%
i 149
 
6.1%
o 144
 
5.9%
s 125
 
5.1%
d 108
 
4.4%
a 107
 
4.4%
p 104
 
4.3%
E 94
 
3.9%
r 91
 
3.7%
Other values (61) 948
38.9%
Cyrillic
ValueCountFrequency (%)
и 34
12.3%
е 26
 
9.4%
р 25
 
9.1%
я 25
 
9.1%
С 19
 
6.9%
а 17
 
6.2%
о 15
 
5.4%
н 12
 
4.3%
с 11
 
4.0%
т 9
 
3.3%
Other values (31) 83
30.1%
Arabic
ValueCountFrequency (%)
ل 7
21.2%
ا 6
18.2%
ة 4
12.1%
ح 3
9.1%
ق 3
9.1%
س 2
 
6.1%
ع 2
 
6.1%
ي 2
 
6.1%
ب 1
 
3.0%
ن 1
 
3.0%
Other values (2) 2
 
6.1%
None
ValueCountFrequency (%)
ü 3
42.9%
ó 2
28.6%
ä 1
 
14.3%
ú 1
 
14.3%
Letterlike Symbols
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
1
100.0%

season
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.962162
Minimum1
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:52.971918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q32
95-th percentile9.8
Maximum2022
Range2021
Interquartile range (IQR)1

Descriptive statistics

Standard deviation294.56703
Coefficient of variation (CV)6.4089027
Kurtosis42.433937
Mean45.962162
Median Absolute Deviation (MAD)0
Skewness6.6310365
Sum8503
Variance86769.732
MonotonicityNot monotonic
2023-08-05T21:56:53.115308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
1 105
56.8%
2 42
 
22.7%
3 9
 
4.9%
4 6
 
3.2%
5 5
 
2.7%
2022 4
 
2.2%
8 2
 
1.1%
7 2
 
1.1%
6 2
 
1.1%
11 2
 
1.1%
Other values (5) 6
 
3.2%
ValueCountFrequency (%)
1 105
56.8%
2 42
 
22.7%
3 9
 
4.9%
4 6
 
3.2%
5 5
 
2.7%
6 2
 
1.1%
7 2
 
1.1%
8 2
 
1.1%
9 2
 
1.1%
10 1
 
0.5%
ValueCountFrequency (%)
2022 4
2.2%
22 1
 
0.5%
19 1
 
0.5%
17 1
 
0.5%
11 2
1.1%
10 1
 
0.5%
9 2
1.1%
8 2
1.1%
7 2
1.1%
6 2
1.1%

number
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)25.0%
Missing5
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean18.083333
Minimum1
Maximum271
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:53.280889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median7
Q314
95-th percentile92.05
Maximum271
Range270
Interquartile range (IQR)10

Descriptive statistics

Standard deviation35.786592
Coefficient of variation (CV)1.978982
Kurtosis23.950564
Mean18.083333
Median Absolute Deviation (MAD)4
Skewness4.4685053
Sum3255
Variance1280.6802
MonotonicityNot monotonic
2023-08-05T21:56:53.437015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
4 21
 
11.4%
6 15
 
8.1%
1 14
 
7.6%
3 14
 
7.6%
2 12
 
6.5%
8 12
 
6.5%
5 12
 
6.5%
7 11
 
5.9%
12 6
 
3.2%
11 5
 
2.7%
Other values (35) 58
31.4%
ValueCountFrequency (%)
1 14
7.6%
2 12
6.5%
3 14
7.6%
4 21
11.4%
5 12
6.5%
6 15
8.1%
7 11
5.9%
8 12
6.5%
9 2
 
1.1%
10 4
 
2.2%
ValueCountFrequency (%)
271 1
0.5%
244 1
0.5%
158 1
0.5%
144 1
0.5%
119 1
0.5%
102 1
0.5%
100 1
0.5%
94 1
0.5%
93 1
0.5%
92 1
0.5%

type
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
regular
180 
insignificant_special
 
4
significant_special
 
1

Length

Max length21
Median length7
Mean length7.3675676
Min length7

Characters and Unicode

Total characters1363
Distinct characters14
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st rowregular
2nd rowregular
3rd rowregular
4th rowregular
5th rowregular

Common Values

ValueCountFrequency (%)
regular 180
97.3%
insignificant_special 4
 
2.2%
significant_special 1
 
0.5%

Length

2023-08-05T21:56:53.585491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-05T21:56:53.710384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 180
97.3%
insignificant_special 4
 
2.2%
significant_special 1
 
0.5%

Most occurring characters

ValueCountFrequency (%)
r 360
26.4%
a 190
13.9%
e 185
13.6%
g 185
13.6%
l 185
13.6%
u 180
13.2%
i 24
 
1.8%
n 14
 
1.0%
s 10
 
0.7%
c 10
 
0.7%
Other values (4) 20
 
1.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1358
99.6%
Connector Punctuation 5
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 360
26.5%
a 190
14.0%
e 185
13.6%
g 185
13.6%
l 185
13.6%
u 180
13.3%
i 24
 
1.8%
n 14
 
1.0%
s 10
 
0.7%
c 10
 
0.7%
Other values (3) 15
 
1.1%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1358
99.6%
Common 5
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 360
26.5%
a 190
14.0%
e 185
13.6%
g 185
13.6%
l 185
13.6%
u 180
13.3%
i 24
 
1.8%
n 14
 
1.0%
s 10
 
0.7%
c 10
 
0.7%
Other values (3) 15
 
1.1%
Common
ValueCountFrequency (%)
_ 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1363
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 360
26.4%
a 190
13.9%
e 185
13.6%
g 185
13.6%
l 185
13.6%
u 180
13.2%
i 24
 
1.8%
n 14
 
1.0%
s 10
 
0.7%
c 10
 
0.7%
Other values (4) 20
 
1.5%

airdate
Date

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2022-12-22 00:00:00
Maximum2022-12-22 00:00:00
2023-08-05T21:56:53.816939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:53.923910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

airtime
Date

MISSING 

Distinct19
Distinct (%)33.3%
Missing128
Missing (%)69.2%
Memory size1.6 KiB
Minimum2023-08-05 00:00:00
Maximum2023-08-05 23:50:00
2023-08-05T21:56:54.047355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:54.188894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
Distinct23
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2022-12-22 00:00:00+00:00
Maximum2022-12-23 00:00:00+00:00
2023-08-05T21:56:54.319195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:54.448750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

runtime
Real number (ℝ)

MISSING 

Distinct57
Distinct (%)36.1%
Missing27
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean41.727848
Minimum3
Maximum240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:54.586774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile7
Q120
median42
Q350.75
95-th percentile79.15
Maximum240
Range237
Interquartile range (IQR)30.75

Descriptive statistics

Standard deviation30.842656
Coefficient of variation (CV)0.73913842
Kurtosis13.867979
Mean41.727848
Median Absolute Deviation (MAD)12
Skewness2.8757495
Sum6593
Variance951.26941
MonotonicityNot monotonic
2023-08-05T21:56:54.752519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45 21
 
11.4%
42 10
 
5.4%
10 9
 
4.9%
20 8
 
4.3%
41 6
 
3.2%
51 6
 
3.2%
7 5
 
2.7%
25 5
 
2.7%
30 5
 
2.7%
40 5
 
2.7%
Other values (47) 78
42.2%
(Missing) 27
 
14.6%
ValueCountFrequency (%)
3 2
 
1.1%
4 1
 
0.5%
5 2
 
1.1%
7 5
2.7%
9 1
 
0.5%
10 9
4.9%
11 2
 
1.1%
12 4
2.2%
15 2
 
1.1%
16 1
 
0.5%
ValueCountFrequency (%)
240 1
0.5%
180 1
0.5%
165 1
0.5%
124 1
0.5%
120 1
0.5%
110 1
0.5%
109 1
0.5%
80 1
0.5%
79 1
0.5%
75 1
0.5%

rating_average
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing185
Missing (%)100.0%
Memory size1.6 KiB

medium
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing119
Missing (%)64.3%
Memory size1.6 KiB
2023-08-05T21:56:54.986230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length73
Mean length73
Min length73

Characters and Unicode

Total characters4818
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/medium_landscape/438/1095209.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/438/1095210.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/medium_landscape/436/1091189.jpg
4th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/436/1091190.jpg
5th rowhttps://static.tvmaze.com/uploads/images/medium_landscape/436/1091174.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090890.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/470/1177057.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/438/1095210.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1091189.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1091190.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1091174.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090984.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090985.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090986.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/medium_landscape/436/1090987.jpg 1
 
1.5%
Other values (56) 56
84.8%
2023-08-05T21:56:55.371418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 462
 
9.6%
a 396
 
8.2%
m 330
 
6.8%
s 330
 
6.8%
t 330
 
6.8%
p 264
 
5.5%
e 264
 
5.5%
. 198
 
4.1%
d 198
 
4.1%
c 198
 
4.1%
Other values (22) 1848
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3366
69.9%
Other Punctuation 726
 
15.1%
Decimal Number 660
 
13.7%
Connector Punctuation 66
 
1.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 396
11.8%
m 330
9.8%
s 330
9.8%
t 330
9.8%
p 264
 
7.8%
e 264
 
7.8%
d 198
 
5.9%
c 198
 
5.9%
i 198
 
5.9%
g 132
 
3.9%
Other values (8) 726
21.6%
Decimal Number
ValueCountFrequency (%)
1 121
18.3%
0 117
17.7%
4 92
13.9%
9 91
13.8%
3 76
11.5%
6 49
7.4%
8 39
 
5.9%
7 34
 
5.2%
5 26
 
3.9%
2 15
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/ 462
63.6%
. 198
27.3%
: 66
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3366
69.9%
Common 1452
30.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 396
11.8%
m 330
9.8%
s 330
9.8%
t 330
9.8%
p 264
 
7.8%
e 264
 
7.8%
d 198
 
5.9%
c 198
 
5.9%
i 198
 
5.9%
g 132
 
3.9%
Other values (8) 726
21.6%
Common
ValueCountFrequency (%)
/ 462
31.8%
. 198
13.6%
1 121
 
8.3%
0 117
 
8.1%
4 92
 
6.3%
9 91
 
6.3%
3 76
 
5.2%
_ 66
 
4.5%
: 66
 
4.5%
6 49
 
3.4%
Other values (4) 114
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4818
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 462
 
9.6%
a 396
 
8.2%
m 330
 
6.8%
s 330
 
6.8%
t 330
 
6.8%
p 264
 
5.5%
e 264
 
5.5%
. 198
 
4.1%
d 198
 
4.1%
c 198
 
4.1%
Other values (22) 1848
38.4%

original
Text

MISSING 

Distinct66
Distinct (%)100.0%
Missing119
Missing (%)64.3%
Memory size1.6 KiB
2023-08-05T21:56:55.628779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length75
Median length75
Mean length75
Min length75

Characters and Unicode

Total characters4950
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)100.0%

Sample

1st rowhttps://static.tvmaze.com/uploads/images/original_untouched/438/1095209.jpg
2nd rowhttps://static.tvmaze.com/uploads/images/original_untouched/438/1095210.jpg
3rd rowhttps://static.tvmaze.com/uploads/images/original_untouched/436/1091189.jpg
4th rowhttps://static.tvmaze.com/uploads/images/original_untouched/436/1091190.jpg
5th rowhttps://static.tvmaze.com/uploads/images/original_untouched/436/1091174.jpg
ValueCountFrequency (%)
https://static.tvmaze.com/uploads/images/original_untouched/436/1090890.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/470/1177057.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/438/1095210.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1091189.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1091190.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1091174.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090984.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090985.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090986.jpg 1
 
1.5%
https://static.tvmaze.com/uploads/images/original_untouched/436/1090987.jpg 1
 
1.5%
Other values (56) 56
84.8%
2023-08-05T21:56:56.008835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 462
 
9.3%
t 396
 
8.0%
a 330
 
6.7%
s 264
 
5.3%
i 264
 
5.3%
o 264
 
5.3%
p 198
 
4.0%
c 198
 
4.0%
. 198
 
4.0%
g 198
 
4.0%
Other values (23) 2178
44.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3498
70.7%
Other Punctuation 726
 
14.7%
Decimal Number 660
 
13.3%
Connector Punctuation 66
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 396
 
11.3%
a 330
 
9.4%
s 264
 
7.5%
i 264
 
7.5%
o 264
 
7.5%
p 198
 
5.7%
c 198
 
5.7%
g 198
 
5.7%
m 198
 
5.7%
e 198
 
5.7%
Other values (9) 990
28.3%
Decimal Number
ValueCountFrequency (%)
1 121
18.3%
0 117
17.7%
4 92
13.9%
9 91
13.8%
3 76
11.5%
6 49
7.4%
8 39
 
5.9%
7 34
 
5.2%
5 26
 
3.9%
2 15
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/ 462
63.6%
. 198
27.3%
: 66
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3498
70.7%
Common 1452
29.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 396
 
11.3%
a 330
 
9.4%
s 264
 
7.5%
i 264
 
7.5%
o 264
 
7.5%
p 198
 
5.7%
c 198
 
5.7%
g 198
 
5.7%
m 198
 
5.7%
e 198
 
5.7%
Other values (9) 990
28.3%
Common
ValueCountFrequency (%)
/ 462
31.8%
. 198
13.6%
1 121
 
8.3%
0 117
 
8.1%
4 92
 
6.3%
9 91
 
6.3%
3 76
 
5.2%
: 66
 
4.5%
_ 66
 
4.5%
6 49
 
3.4%
Other values (4) 114
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4950
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 462
 
9.3%
t 396
 
8.0%
a 330
 
6.7%
s 264
 
5.3%
i 264
 
5.3%
o 264
 
5.3%
p 198
 
4.0%
c 198
 
4.0%
. 198
 
4.0%
g 198
 
4.0%
Other values (23) 2178
44.0%

_links_self
Text

UNIQUE 

Distinct185
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:56.236408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters7215
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique185 ?
Unique (%)100.0%

Sample

1st rowhttps://api.tvmaze.com/episodes/2401588
2nd rowhttps://api.tvmaze.com/episodes/2164183
3rd rowhttps://api.tvmaze.com/episodes/2575563
4th rowhttps://api.tvmaze.com/episodes/2575564
5th rowhttps://api.tvmaze.com/episodes/2443147
ValueCountFrequency (%)
https://api.tvmaze.com/episodes/2401588 1
 
0.5%
https://api.tvmaze.com/episodes/2448457 1
 
0.5%
https://api.tvmaze.com/episodes/2449288 1
 
0.5%
https://api.tvmaze.com/episodes/2575563 1
 
0.5%
https://api.tvmaze.com/episodes/2575564 1
 
0.5%
https://api.tvmaze.com/episodes/2443147 1
 
0.5%
https://api.tvmaze.com/episodes/2443148 1
 
0.5%
https://api.tvmaze.com/episodes/2424822 1
 
0.5%
https://api.tvmaze.com/episodes/2452406 1
 
0.5%
https://api.tvmaze.com/episodes/2452409 1
 
0.5%
Other values (175) 175
94.6%
2023-08-05T21:56:56.595448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 740
 
10.3%
p 555
 
7.7%
s 555
 
7.7%
e 555
 
7.7%
t 555
 
7.7%
o 370
 
5.1%
a 370
 
5.1%
i 370
 
5.1%
. 370
 
5.1%
m 370
 
5.1%
Other values (16) 2405
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4625
64.1%
Other Punctuation 1295
 
17.9%
Decimal Number 1295
 
17.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
p 555
12.0%
s 555
12.0%
e 555
12.0%
t 555
12.0%
o 370
8.0%
a 370
8.0%
i 370
8.0%
m 370
8.0%
h 185
 
4.0%
d 185
 
4.0%
Other values (3) 555
12.0%
Decimal Number
ValueCountFrequency (%)
2 280
21.6%
4 263
20.3%
5 140
10.8%
1 116
9.0%
6 105
 
8.1%
3 100
 
7.7%
7 82
 
6.3%
0 75
 
5.8%
9 68
 
5.3%
8 66
 
5.1%
Other Punctuation
ValueCountFrequency (%)
/ 740
57.1%
. 370
28.6%
: 185
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 4625
64.1%
Common 2590
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 740
28.6%
. 370
14.3%
2 280
 
10.8%
4 263
 
10.2%
: 185
 
7.1%
5 140
 
5.4%
1 116
 
4.5%
6 105
 
4.1%
3 100
 
3.9%
7 82
 
3.2%
Other values (3) 209
 
8.1%
Latin
ValueCountFrequency (%)
p 555
12.0%
s 555
12.0%
e 555
12.0%
t 555
12.0%
o 370
8.0%
a 370
8.0%
i 370
8.0%
m 370
8.0%
h 185
 
4.0%
d 185
 
4.0%
Other values (3) 555
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 740
 
10.3%
p 555
 
7.7%
s 555
 
7.7%
e 555
 
7.7%
t 555
 
7.7%
o 370
 
5.1%
a 370
 
5.1%
i 370
 
5.1%
. 370
 
5.1%
m 370
 
5.1%
Other values (16) 2405
33.3%
Distinct111
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2023-08-05T21:56:56.820581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length34
Mean length33.972973
Min length32

Characters and Unicode

Total characters6285
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique82 ?
Unique (%)44.3%

Sample

1st rowhttps://api.tvmaze.com/shows/7847
2nd rowhttps://api.tvmaze.com/shows/48151
3rd rowhttps://api.tvmaze.com/shows/55724
4th rowhttps://api.tvmaze.com/shows/55724
5th rowhttps://api.tvmaze.com/shows/59484
ValueCountFrequency (%)
https://api.tvmaze.com/shows/50036 8
 
4.3%
https://api.tvmaze.com/shows/62659 8
 
4.3%
https://api.tvmaze.com/shows/53449 8
 
4.3%
https://api.tvmaze.com/shows/64517 8
 
4.3%
https://api.tvmaze.com/shows/65966 7
 
3.8%
https://api.tvmaze.com/shows/66165 6
 
3.2%
https://api.tvmaze.com/shows/55631 6
 
3.2%
https://api.tvmaze.com/shows/47480 6
 
3.2%
https://api.tvmaze.com/shows/66199 4
 
2.2%
https://api.tvmaze.com/shows/65471 4
 
2.2%
Other values (101) 120
64.9%
2023-08-05T21:56:57.199771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 740
 
11.8%
s 555
 
8.8%
t 555
 
8.8%
h 370
 
5.9%
p 370
 
5.9%
a 370
 
5.9%
. 370
 
5.9%
o 370
 
5.9%
m 370
 
5.9%
6 213
 
3.4%
Other values (16) 2002
31.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4070
64.8%
Other Punctuation 1295
 
20.6%
Decimal Number 920
 
14.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 555
13.6%
t 555
13.6%
h 370
9.1%
p 370
9.1%
a 370
9.1%
o 370
9.1%
m 370
9.1%
e 185
 
4.5%
w 185
 
4.5%
c 185
 
4.5%
Other values (3) 555
13.6%
Decimal Number
ValueCountFrequency (%)
6 213
23.2%
5 139
15.1%
4 120
13.0%
3 87
9.5%
1 80
 
8.7%
9 78
 
8.5%
2 55
 
6.0%
7 53
 
5.8%
0 52
 
5.7%
8 43
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 740
57.1%
. 370
28.6%
: 185
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 4070
64.8%
Common 2215
35.2%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 740
33.4%
. 370
16.7%
6 213
 
9.6%
: 185
 
8.4%
5 139
 
6.3%
4 120
 
5.4%
3 87
 
3.9%
1 80
 
3.6%
9 78
 
3.5%
2 55
 
2.5%
Other values (3) 148
 
6.7%
Latin
ValueCountFrequency (%)
s 555
13.6%
t 555
13.6%
h 370
9.1%
p 370
9.1%
a 370
9.1%
o 370
9.1%
m 370
9.1%
e 185
 
4.5%
w 185
 
4.5%
c 185
 
4.5%
Other values (3) 555
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6285
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 740
 
11.8%
s 555
 
8.8%
t 555
 
8.8%
h 370
 
5.9%
p 370
 
5.9%
a 370
 
5.9%
. 370
 
5.9%
o 370
 
5.9%
m 370
 
5.9%
6 213
 
3.4%
Other values (16) 2002
31.9%

summary
Text

MISSING 

Distinct63
Distinct (%)100.0%
Missing122
Missing (%)65.9%
Memory size1.6 KiB
2023-08-05T21:56:57.470023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length834
Median length159
Mean length194.65079
Min length44

Characters and Unicode

Total characters12263
Distinct characters77
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)100.0%

Sample

1st row<p>Dongbaek visits a fortunes teller seeking answers. Shortly after, a spirit possesses his body. </p>
2nd row<p>Denis has a breakdown.  Min gets injured protecting Dongbaek. </p>
3rd row<p>Mu Yeong goes to Seon Heo's house to pack up his things, but Seon Heo has something he suddenly wants to tell Mu Yeong.</p>
4th row<p>Far from land, Arthur Wilde and his team of scientists celebrate the culmination of decades of research: a solution to climate change. Then, a gruesome murder – eerily similar to Wilde's South Pole nightmare – occurs onboard.</p>
5th row<p>Zach goes missing before he can release the DNA results from Kowalski's murder. Yuto brings Wilde the surprising results of his web search. Olivia escalates her search for the famous scientist.</p>
ValueCountFrequency (%)
the 124
 
6.1%
and 77
 
3.8%
to 75
 
3.7%
of 51
 
2.5%
a 45
 
2.2%
in 30
 
1.5%
for 21
 
1.0%
on 18
 
0.9%
as 16
 
0.8%
his 16
 
0.8%
Other values (1028) 1545
76.6%
2023-08-05T21:56:57.924225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1948
15.9%
e 1149
 
9.4%
t 788
 
6.4%
a 777
 
6.3%
n 659
 
5.4%
o 648
 
5.3%
i 646
 
5.3%
s 645
 
5.3%
r 604
 
4.9%
h 480
 
3.9%
Other values (67) 3919
32.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9166
74.7%
Space Separator 1956
 
16.0%
Uppercase Letter 439
 
3.6%
Other Punctuation 372
 
3.0%
Math Symbol 279
 
2.3%
Dash Punctuation 25
 
0.2%
Decimal Number 16
 
0.1%
Close Punctuation 5
 
< 0.1%
Open Punctuation 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1149
12.5%
t 788
 
8.6%
a 777
 
8.5%
n 659
 
7.2%
o 648
 
7.1%
i 646
 
7.0%
s 645
 
7.0%
r 604
 
6.6%
h 480
 
5.2%
l 369
 
4.0%
Other values (17) 2401
26.2%
Uppercase Letter
ValueCountFrequency (%)
A 51
 
11.6%
S 40
 
9.1%
T 39
 
8.9%
C 31
 
7.1%
W 30
 
6.8%
M 22
 
5.0%
R 21
 
4.8%
L 20
 
4.6%
H 19
 
4.3%
J 18
 
4.1%
Other values (16) 148
33.7%
Other Punctuation
ValueCountFrequency (%)
, 126
33.9%
. 110
29.6%
/ 70
18.8%
' 40
 
10.8%
; 9
 
2.4%
? 6
 
1.6%
! 6
 
1.6%
: 3
 
0.8%
" 2
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 7
43.8%
1 3
18.8%
5 3
18.8%
0 2
 
12.5%
3 1
 
6.2%
Math Symbol
ValueCountFrequency (%)
> 139
49.8%
< 139
49.8%
+ 1
 
0.4%
Dash Punctuation
ValueCountFrequency (%)
- 16
64.0%
6
 
24.0%
3
 
12.0%
Space Separator
ValueCountFrequency (%)
1948
99.6%
  8
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9605
78.3%
Common 2658
 
21.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1149
12.0%
t 788
 
8.2%
a 777
 
8.1%
n 659
 
6.9%
o 648
 
6.7%
i 646
 
6.7%
s 645
 
6.7%
r 604
 
6.3%
h 480
 
5.0%
l 369
 
3.8%
Other values (43) 2840
29.6%
Common
ValueCountFrequency (%)
1948
73.3%
> 139
 
5.2%
< 139
 
5.2%
, 126
 
4.7%
. 110
 
4.1%
/ 70
 
2.6%
' 40
 
1.5%
- 16
 
0.6%
; 9
 
0.3%
  8
 
0.3%
Other values (14) 53
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12245
99.9%
None 9
 
0.1%
Punctuation 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1948
15.9%
e 1149
 
9.4%
t 788
 
6.4%
a 777
 
6.3%
n 659
 
5.4%
o 648
 
5.3%
i 646
 
5.3%
s 645
 
5.3%
r 604
 
4.9%
h 480
 
3.9%
Other values (63) 3901
31.9%
None
ValueCountFrequency (%)
  8
88.9%
í 1
 
11.1%
Punctuation
ValueCountFrequency (%)
6
66.7%
3
33.3%

Interactions

2023-08-05T21:56:49.423218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:47.432357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:47.908233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.427553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.937787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:49.514918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:47.521131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.008576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.524957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:49.034802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:49.615730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:47.621440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.111422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.634887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:49.133663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:49.719531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:47.727076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.230360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.742190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:49.242145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:49.824743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:47.819070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.327226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:48.841504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-08-05T21:56:49.331939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-08-05T21:56:58.041548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
idid_embeddedseasonnumberruntimetype
id1.0000.4610.0120.046-0.2380.000
id_embedded0.4611.000-0.557-0.049-0.1910.208
season0.012-0.5571.0000.0910.1100.000
number0.046-0.0490.0911.000-0.2181.000
runtime-0.238-0.1910.110-0.2181.0000.422
type0.0000.2080.0001.0000.4221.000

Missing values

2023-08-05T21:56:49.972709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-05T21:56:50.224804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-08-05T21:56:50.399410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

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